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基于神经网络的丙烯腈流化床反应器的离线模拟与优化
引用本文:李伟,张述伟,李燕,张沛存,王效斗. 基于神经网络的丙烯腈流化床反应器的离线模拟与优化[J]. 中国化学工程学报, 2002, 10(2): 198-201
作者姓名:李伟  张述伟  李燕  张沛存  王效斗
作者单位:SchoolofChemicalEngineering,DelianUniversityofTechnology,Dalian116012,China
摘    要:A mathematical model is developed for an industrial acrylonitrile fluidized-bed reactor based on artificial neural networks.A new algorithm,which combines the characteristics of both genetic algorithm(GA) and generalized delta-rule(GDR) is used to train artificial neural network (ANN) in order to avoid search terminated at a local optimal solution.For searching the global optimum,a new algorithm called SM-GA,incorporating advantages of both simplex method (SM) and GA, is proposed and applied to optimize the operating conditions of an acrylonitrile fluidized-bed reactor in industry.

关 键 词:人工神经网络 离线最佳化 丙烯腈 流化床反应器 模拟最佳化
修稿时间: 

Simulation and Off-line Optimization of an Acrylonitrile Fluidized-bed Reactor Based on Artificial Neural Network
LI Wei,ZHANG shuwei,LI Yan,ZHANG Peicun,WANG Xiaodou. Simulation and Off-line Optimization of an Acrylonitrile Fluidized-bed Reactor Based on Artificial Neural Network[J]. Chinese Journal of Chemical Engineering, 2002, 10(2): 198-201
Authors:LI Wei  ZHANG shuwei  LI Yan  ZHANG Peicun  WANG Xiaodou
Abstract:A mathematical model is developed for an industrial acrylonitrile fluidized-bed reactor based on artificial neural networks. A new algorithm, which combines the characteristics of both genetic algorithm (GA) and generalized delta-rule (GDR) is used to train artificial neural network (ANN) in order to avoid search terminated at a local optimal solution. For searching the global optimum, a new algorithm called SM-GA, incorporating advantages of both simplex method (SM )and GA, is proposed and applied to optimize the operating conditions of an acrylonitrile fluidized-bed reactor in industry.
Keywords:simulation  optimization   artificial neural network   genetic algorithm   simplex method   fluidized-bed reactor   acrylonitrile
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